Developed in partnership with 91短视频 Grossman School of Medicine investigators, the tool predicted risk among more than 6.4 million people across the world.
Credit: Getty Images / Fizkes
A tool developed by the American Heart Association (AHA), already proven to accurately predict heart disease risk for Americans, can also be applied to the global population, a new study led by 91短视频 Langone Health shows.
Accurate identification of those at high cardiovascular disease (CVD) risk enables targeted use of preventive therapies, such as lipid-lowering medications and intensive blood pressure targets, and can move patients to quit smoking, eat better, and exercise, the study authors say.
The study addresses the AHA鈥檚 risk-prediction tool, Predicting Risk of Cardiovascular Disease Events (PREVENT), which was developed in partnership with 91短视频 Grossman School of Medicine investigators. Published in 2023, PREVENT was designed to predict a person鈥檚 10- and 30-year total risk for CVD, time intervals long enough to include a meaningful amount of risk and treatment benefit. Total risk includes risk for heart failure along with the originally measured risks for heart attack and stroke, because there are now effective therapies available that aid the prevention of all three conditions.
Use of the PREVENT tool to guide drug treatment, as well as to guide clinical trial design for people with hypertension and high cholesterol, was recently incorporated for the first time into the treatment guidelines of several US medical societies, based on studies that had included more than 6 million Americans. What was needed, say the authors, was strong evidence across a wide range of settings and clinical trials to support its adoption as part of clinical practice worldwide.
, the work found that the tool accurately predicted risk for cardiovascular disease among more than 6.4 million people from North America, Europe, Asia, and other regions. It was particularly effective for predicting heart failure and for patients at low to moderate risk, the group for whom flagging risk early can trigger treatment and lifestyle changes in time to avert severe disease. Adding a measure of kidney health made the predictions even more accurate.
鈥淎 key barrier to the international adoption of PREVENT is the uncertainty felt by physicians that the tool is generalizable across patient groups in different geographical areas,鈥 said senior study author , the founding director of the at 91短视频 Langone. He is also the 鈥檚 Terry and Mel Karmazin Professor of Population Health, as well as a professor in the .
Most Effective Where It Matters
The study authors analyzed data from 6.8 million patients who did not have cardiovascular disease at the beginning of 62 studies. These included 44 cohorts from North America, Europe, and Asia, and 18 multiregional randomized trials that included 53,002 patients. The team was able to see how well predictions made by the tool at the study鈥檚 start were borne out by comparing them with the approximately 300,000 CVD events that participants experienced over the next 5.5 years.
For the study, researchers used discrimination and calibration, two fundamental metrics that evaluate the performance of disease risk prediction models. Discrimination measures how well a model separates patients who will go on to develop a disease from those who do not. In the current global analysis, PREVENT鈥檚 discrimination was 鈥渟uperior,鈥 say the authors, in studies that focused on lower-risk patients, supporting the broader adoption of PREVENT in primary care populations, where some patients have very low risk and others have moderate to high risk, leading to different treatment implications.
In terms of kidney health, the model鈥檚 prediction performance improved when it accounted for a person鈥檚 risk of albuminuria, a condition where urine protein levels are elevated due to kidney damage, often by high blood pressure or diabetes. In terms of discrimination, adding kidney risk to the PREVENT model brought about a statistically significant improvement in prediction accuracy.
Calibration measures how accurately the predicted probabilities match the actual outcomes for each patient down the road. Calibration measures for PREVENT were much better than those of an older model called Pooled Cohort Equation (PCE), which predicted risk of about half what it turned out to be.
鈥淏ecause PREVENT guidelines typically form the basis for national policies that guide treatment decisions, painstaking validation of PREVENT across diverse populations was critical,鈥 said Dr. Coresh. 鈥淥ur large-scale study confirms that PREVENT is a reliable tool that can be used globally.鈥
Along with Dr. Coresh, study authors from 91短视频 Langone were ; Yingying Sang, MSc; ; and .
The study was conducted by the Chronic Kidney Disease (CKD) Prognosis Consortium, which is funded in part by the grant R01DK100446 from the National Institute of Diabetes and Digestive and Kidney Diseases, part of the National Institutes of Health. Also providing support was the National Kidney Foundation.
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